SpliceMap

SpliceMap detects splice junctions from RNA sequencing (RNA-seq) data to identify alternative splicing events using second-generation sequencing reads.

Key Features:

• Annotation-Independent Detection: Operates without reliance on pre-existing gene structure annotations, enabling identification of novel splice junctions.
• Long-Read Handling: Processes long reads of 50 to 100 nucleotides (nt) typical of second-generation sequencing platforms.
• Paired-Read Information Utilization: Exploits paired-read information to improve accuracy of splice junction mapping.
• Reliability Indicators: Outputs parameters that indicate confidence of predicted splice junctions to assist filtering of false positives.
• High-Throughput Scaling: Scales to large RNA-seq datasets and high sequencing depths typical of second-generation sequencing studies.
• Sensitivity Improvement: Reports an enhanced sensitivity of 12% over current techniques while maintaining specificity.

Scientific Applications:

• Alternative Splicing Analysis: Detection and characterization of alternative splicing events from RNA-seq data.
• Discovery of Novel Junctions: Identification of common and rare splice junctions in unannotated or sparsely annotated genomic regions.
• High-Depth RNA-seq Studies: Application to large datasets, exemplified by validation on 23 million paired 50-nt reads from human brain tissue.

Methodology:

Annotation-independent computational algorithms analyze paired-end RNA-seq reads (50–100 nt) and incorporate reliability metrics into predicted splice junction outputs.